Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

An Efficient Loom of Vegetation Exploration in Remote Sensing Images Using Object-Based Threshold Classification

Author : Dr. D. Napoleon 1 S. Dhanya Shree 2

Date of Publication :9th November 2017

Abstract: In recent years, despite the increased availability of high resolution satellite images there is a growth of extensive research in field of remote sensing image analysis. As such, there is a need for simple and efficient image classification technique to classify the remote data. The input data is obtained from the Landsat-7 satellite, which formulates to accomplish remote sensing image classification. This research work has been done with Object Based Threshold Classification to find the vegetation exploration with Normalized Vegetation Index, Near Infra-Red and visible brightness. The resultant land cover image with Object-Based Threshold The classification has more data classes and higher resolution than the normal image classification techniques. This research paper discusses an efficient and effective use of image classification which helps to classify the vegetation exploration in remote sensing images.

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